公开(公告)号：US20210209449A1

公开(公告)日：2021-07-08

申请号：US17209601

申请日：2021-03-23

申请人： UiPath, Inc.

发明人： Mircea Neagovici ,  Stefan ADAM ,  Virgil Tudor ,  Dragos Bobolea

IPC分类号： G06N3/04 ,  G06F17/18 ,  G06F17/15 ,  G06T7/11 ,  G06F9/455

摘要： Graphical elements in a user interface (UI) may be detected in robotic process automation (RPA) using convolutional neural networks (CNNs). Such processes may be particularly well-suited for detecting graphical elements that are too small to be detected using conventional techniques. The accuracy of detecting graphical elements (e.g., control objects) may be enhanced by providing neural network-based processing that is robust to changes in various UI factors, such as different resolutions, different operating system (OS) scaling factors, different dots-per-inch (DPI) settings, and changes due to UI customization of applications and websites, for example.

公开(公告)号：US11599775B2

公开(公告)日：2023-03-07

申请号：US17209601

申请日：2021-03-23

申请人： UiPath, Inc.

发明人： Mircea Neagovici ,  Stefan Adam ,  Virgil Tudor ,  Dragos Bobolea

IPC分类号： G06F17/18 ,  G06N3/04 ,  G06F9/455 ,  G06F17/15 ,  G06T7/11

摘要： Graphical elements in a user interface (UI) may be detected in robotic process automation (RPA) using convolutional neural networks (CNNs). Such processes may be particularly well-suited for detecting graphical elements that are too small to be detected using conventional techniques. The accuracy of detecting graphical elements (e.g., control objects) may be enhanced by providing neural network-based processing that is robust to changes in various UI factors, such as different resolutions, different operating system (OS) scaling factors, different dots-per-inch (DPI) settings, and changes due to UI customization of applications and websites, for example.

公开(公告)号：US10990876B1

公开(公告)日：2021-04-27

申请号：US16595727

申请日：2019-10-08

申请人： UiPath, Inc.

发明人： Mircea Neagovici ,  Stefan Adam ,  Virgil Tudor ,  Dragos Bobolea

IPC分类号： G06N3/02 ,  G06N3/04 ,  G06F9/455 ,  G06F17/18 ,  G06F17/15 ,  G06T7/11

摘要： Graphical elements in a user interface (UI) may be detected in robotic process automation (RPA) using convolutional neural networks (CNNs). Such processes may be particularly well-suited for detecting graphical elements that are too small to be detected using conventional techniques. The accuracy of detecting graphical elements (e.g., control objects) may be enhanced by providing neural network-based processing that is robust to changes in various UI factors, such as different resolutions, different operating system (OS) scaling factors, different dots-per-inch (DPI) settings, and changes due to UI customization of applications and websites, for example.